安装Tornado
省事点可以直接用grequests库，下面用的是tornado的异步client。 异步用到了tornado，根据官方文档的例子修改得到一个简单的异步爬虫类。可以参考下最新的文档学习下。
pip install tornado

异步爬虫

#!/usr/bin/env python
# -*- coding:utf-8 -*-

import time
from datetime import timedelta
from tornado import httpclient, gen, ioloop, queues
import traceback


class AsySpider(object):
 """A simple class of asynchronous spider."""
 def __init__(self, urls, concurrency=10, **kwargs):
 urls.reverse()
 self.urls = urls
 self.concurrency = concurrency
 self._q = queues.Queue()
 self._fetching = set()
 self._fetched = set()

 def fetch(self, url, **kwargs):
 fetch = getattr(httpclient.AsyncHTTPClient(), 'fetch')
 return fetch(url, **kwargs)

 def handle_html(self, url, html):
 """handle html page"""
 print(url)

 def handle_response(self, url, response):
 """inherit and rewrite this method"""
 if response.code == 200:
 self.handle_html(url, response.body)

 elif response.code == 599: # retry
 self._fetching.remove(url)
 self._q.put(url)

 @gen.coroutine
 def get_page(self, url):
 try:
 response = yield self.fetch(url)
 print('######fetched %s' % url)
 except Exception as e:
 print('Exception: %s %s' % (e, url))
 raise gen.Return(e)
 raise gen.Return(response)

 @gen.coroutine
 def _run(self):
 @gen.coroutine
 def fetch_url():
 current_url = yield self._q.get()
 try:
 if current_url in self._fetching:
 return

 print('fetching****** %s' % current_url)
 self._fetching.add(current_url)

 response = yield self.get_page(current_url)
 self.handle_response(current_url, response) # handle reponse

 self._fetched.add(current_url)

 for i in range(self.concurrency):
 if self.urls:
 yield self._q.put(self.urls.pop())

 finally:
 self._q.task_done()

 @gen.coroutine
 def worker():
 while True:
 yield fetch_url()

 self._q.put(self.urls.pop()) # add first url

 # Start workers, then wait for the work queue to be empty.
 for _ in range(self.concurrency):
 worker()

 yield self._q.join(timeout=timedelta(seconds=300000))
 assert self._fetching == self._fetched

 def run(self):
 io_loop = ioloop.IOLoop.current()
 io_loop.run_sync(self._run)


class MySpider(AsySpider):

 def fetch(self, url, **kwargs):
 """重写父类fetch方法可以添加cookies，headers，timeout等信息"""
 cookies_str = "PHPSESSID=j1tt66a829idnms56ppb70jri4; pspt=%7B%22id%22%3A%2233153%22%2C%22pswd%22%3A%228835d2c1351d221b4ab016fbf9e8253f%22%2C%22_code%22%3A%22f779dcd011f4e2581c716d1e1b945861%22%7D; key=%E9%87%8D%E5%BA%86%E5%95%84%E6%9C%A8%E9%B8%9F%E7%BD%91%E7%BB%9C%E7%A7%91%E6%8A%80%E6%9C%%E9%99%90%E5%85%AC%E5%8F%B8; think_language=zh-cn; SERVERID=a66d7d08fa1c8b2e37dbdc6ffff82d9e|1444973193|1444967835; CNZZDATA1254842228=14338393-1442810831-%7C1444972138" # 从浏览器拷贝cookie字符串
 headers = {
 'User-Agent': 'mozilla/5.0 (compatible; baiduspider/2.0; +http://www.baidu.com/search/spider.html)',
 'cookie': cookies_str
 }
 return super(MySpider, self).fetch( # 参数参考tornado文档
 url, headers=headers, request_timeout=1
 )

 def handle_html(self, url, html):
 print(url, html)


def main():
 urls = []
 for page in range(1, 100):
 urls.append('http://www.baidu.com?page=%s' % page)
 s = MySpider(urls)
 s.run()


if __name__ == '__main__':
 main()

可以继承这个类，塞一些url进去，然后重写handle_page处理得到的页面。

异步＋多进程爬虫
还可以再变态点，加个进程池，使用了multiprocessing模块。效率飕飕的,

#!/usr/bin/env python
# -*- coding:utf-8 -*-

import time
from multiprocessing import Pool
from datetime import timedelta
from tornado import httpclient, gen, ioloop, queues


class AsySpider(object):
 """A simple class of asynchronous spider."""
 def __init__(self, urls, concurrency):
 urls.reverse()
 self.urls = urls
 self.concurrency = concurrency
 self._q = queues.Queue()
 self._fetching = set()
 self._fetched = set()

 def handle_page(self, url, html):
 filename = url.rsplit('/', 1)[1]
 with open(filename, 'w+') as f:
 f.write(html)

 @gen.coroutine
 def get_page(self, url):
 try:
 response = yield httpclient.AsyncHTTPClient().fetch(url)
 print('######fetched %s' % url)
 except Exception as e:
 print('Exception: %s %s' % (e, url))
 raise gen.Return('')
 raise gen.Return(response.body)

 @gen.coroutine
 def _run(self):

 @gen.coroutine
 def fetch_url():
 current_url = yield self._q.get()
 try:
 if current_url in self._fetching:
 return

 print('fetching****** %s' % current_url)
 self._fetching.add(current_url)
 html = yield self.get_page(current_url)
 self._fetched.add(current_url)

 self.handle_page(current_url, html)

 for i in range(self.concurrency):
 if self.urls:
 yield self._q.put(self.urls.pop())

 finally:
 self._q.task_done()

 @gen.coroutine
 def worker():
 while True:
 yield fetch_url()

 self._q.put(self.urls.pop())

 # Start workers, then wait for the work queue to be empty.
 for _ in range(self.concurrency):
 worker()
 yield self._q.join(timeout=timedelta(seconds=300000))
 assert self._fetching == self._fetched

 def run(self):
 io_loop = ioloop.IOLoop.current()
 io_loop.run_sync(self._run)


def run_spider(beg, end):
 urls = []
 for page in range(beg, end):
 urls.append('http://127.0.0.1/%s.htm' % page)
 s = AsySpider(urls, 10)
 s.run()


def main():
 _st = time.time()
 p = Pool()
 all_num = 73000
 num = 4 # number of cpu cores
 per_num, left = divmod(all_num, num)
 s = range(0, all_num, per_num)
 res = []
 for i in range(len(s)-1):
 res.append((s[i], s[i+1]))
 res.append((s[len(s)-1], all_num))
 print res

 for i in res:
 p.apply_async(run_spider, args=(i[0], i[1],))
 p.close()
 p.join()

 print time.time()-_st


if __name__ == '__main__':
 main()

多线程爬虫
线程池实现.

#!/usr/bin/env python
# -*- coding:utf-8 -*-
import Queue
import sys
import requests
import os
import threading
import time

class Worker(threading.Thread): # 处理工作请求
 def __init__(self, workQueue, resultQueue, **kwds):
 threading.Thread.__init__(self, **kwds)
 self.setDaemon(True)
 self.workQueue = workQueue
 self.resultQueue = resultQueue


 def run(self):
 while 1:
 try:
 callable, args, kwds = self.workQueue.get(False) # get task
 res = callable(*args, **kwds)
 self.resultQueue.put(res) # put result
 except Queue.Empty:
 break

class WorkManager: # 线程池管理,创建
 def __init__(self, num_of_workers=10):
 self.workQueue = Queue.Queue() # 请求队列
 self.resultQueue = Queue.Queue() # 

输出结果的队列 self.workers = [] self._recruitThreads(num_of_workers) def _recruitThreads(self, num_of_workers): for i in range(num_of_workers): worker = Worker(self.workQueue, self.resultQueue) # 创建工作线程 self.workers.append(worker) # 加入到线程队列 def start(self): for w in self.workers: w.start() def wait_for_complete(self): while len(self.workers): worker = self.workers.pop() # 从池中取出一个线程处理请求 worker.join() if worker.isAlive() and not self.workQueue.empty(): self.workers.append(worker) # 重新加入线程池中 print 'All jobs were complete.' def add_job(self, callable, *args, **kwds): self.workQueue.put((callable, args, kwds)) # 向工作队列中加入请求 def get_result(self, *args, **kwds): return self.resultQueue.get(*args, **kwds) def download_file(url): #print 'beg download', url requests.get(url).text def main(): try: num_of_threads = int(sys.argv[1]) except: num_of_threads = 10 _st = time.time() wm = WorkManager(num_of_threads) print num_of_threads urls = ['http://www.baidu.com'] * 1000 for i in urls: wm.add_job(download_file, i) wm.start() wm.wait_for_complete() print time.time() - _st if __name__ == '__main__': main()

这三种随便一种都有很高的效率，但是这么跑会给网站服务器不小的压力，尤其是小站点，还是有点节操为好。

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